Physiological conditions frequently involve several different counter-acting and balanced biochemical processes. Under pathological conditions the dynamics and/or the balance of such usually balanced physiological process is/are no longer given. Thus, in the assessment of a physiological condition, it might be desirable to provide a correlation of these different counter-acting biochemical processes to this physiological condition. This might be particularly useful in classifying or grouping of individuals, in the assessment of physiological and pathological conditions, in the monitoring of the efficacy of therapeutic regimens, in the scientific presentation of complex coherences, etc.
An example of a physiological condition that is based on counter-acting physiological processes and under normal circumstances is well-balanced is bone metabolism. The dynamic manner of bone remodeling results from two counter-acting and balanced processes: bone formation and bone resorption. To quite some extend these processes are reflected by biochemical markers of bone turnover, which can be measured in plasma, serum and urine. Characteristics of bone markers as well as their clinical use have been extensively reviewed (Christenson, Clin Biochem 30 (1997), 573-593; Garnero & Delmas, Endocrinol Metab Clin North Am 27 (1998), 303-323; Delmas et al., Osteoporos Int 11 (Suppl. 6) (2000), S2-17; Seibel, Endocrinol Metab Clin North Am 32 (2003), 83-113), Seibel, J Endocrinol Invest 26 (2003), 464-471; Meier et al., Clin Endocr 63 (2005), 603-616). For clinical purposes a distinction is made between markers of bone formation and markers of bone resorption. In postmenopausal women, high bone turnover, often is associated with a significantly increased loss in bone mass as compared to the bone loss for women having a normal or low bone turnover. High, normal, or low bone turnover usually are paralleled by increased levels of bone markers, normal levels of bone markers or lower than normal levels of bone markers, respectively (Garnero et al., J Bone Miner Res 14 (1999), 1614-1621; Srivastava et al., Curr Med Res Opin 21 (2005), 1015-1026). High concentrations of bone turnover markers were associated with an increased bone loss in the hip, spine and femoral neck compared with low levels (Chesnut et al., Am J Med 102 (1997), 29-37, Bauer et al., J Bone Miner Res 14 (1999), 1404-1410; Iki et al., Osteoporos Int 17 (2006), 1086-1095; Lenora et al., Osteoporos Int 18 (2007), 1297-1305). The classification of women having elevated bone turnover by levels of resorption and formation markers remained rather stable over 4 years. Elevated turnover may predict progression to osteoporosis in osteopenic women (Garnero et al., J Bone Min Res 18 (2003), 1789-1794; Iki et al., J Bone Miner Metab 25 (2007), 122-129).
Importantly, elevated bone markers are an independent risk factor for fractures, additive to bone mineral density (BMD) (Garnero et al, J Bone Miner Res 11 (1996), 1531-1538; van Daele et al., Brit Med J 312 (1996), 482-483; Ross, J Clin Densitometry 2 (1999), 285-294; Garnero et al., J Bone Miner Res 15 (2000), 1526-1536; Chapurlat et al., Bone 27 (2000), 283-286; Hannon & Eastell, J Brit Menopaus Soc 9 (2003), 10-15; Bruyere et al., Maturitas 44 (2003), 259-265; Gerdhem et al., J Bone Mineral Res 19 (2004), 386-393; Meier et al., J Bone Miner Res 20 (2005), 579-587). This was observed especially with resorption markers. Relating the concentrations of formation markers to fracture risk has given conflicting findings (Gerdhem et al. (2004), supra; Gundberg, Clin Lab Med 20 (2000), 489-501).
The main interest in bone markers results from the failure of BMD measurement in monitoring the efficacy of treatment against osteoporosis in the individual patient (Stepan, J Endocrinol Invest 26 (2003), 458-463). Changes in BMD due to anti-resorptive or anabolic medications are rather small and become detectable only after at least 1 to 2 years of treatment. However, in clinical practice it is desirable to detect effectiveness of treatment within a few months. An early prediction of BMD response by bone markers became evident from intervention studies with hormone replacement therapy and bisphoshonates (Chesnut et al. (1997), supra; (Garnero et al., J Clin Endocr Metab 79 (1994), 1693-1700; Christgau et al., Bone 26 (2000), 505-511; Greenspan et al., J Clin Endocr Metab 85 (2000), 3537-3540; Christiansen et al., Osteoporos Int 14 (2003), 609-613; Raisz et al., Osteoporos Int 11 (2000), 615-620). While type I collagen derived resorption markers showed a fast response at the latest within 3 to 6 month of anti resorptive therapy, a somewhat delayed decrease in concentrations was observed with formation markers (Garnero et al. (1994), supra; Christiansen et al. (2003), supra; Raisz et al. (2000), supra). In therapy responders both marker types finally declined to normal premenopausal ranges, indicating a normalization of bone turnover. A disturbed balance between markers of bone formation and markers of bone resorption was also observed in anabolic therapy regimens by Teripatide (Dobnig et al., J Clin Endocrinol Metab 90 (2005), 3970-3977).
There is strong evidence from intervention studies that a surveillance of therapy in osteoporotic patients by bone markers is helpful to select early responders and non-responders. However, the interpretation of bone marker data is somewhat cumbersome. The marker concentrations have to be considered in relation to age and gender specific reference ranges and in connection to previous medical reports. In place of the numeric concentration results of the biomarkers, it would be preferable to gain a direct insight into the balance and rate of bone turnover, which are the leading factors to estimate fracture risk, dynamics of bone turnover and prognosis.
WO 96/12187 discloses a diagnostic method wherein the concentration of a set of biomarkers known to be associated with the disease is measured, the digitized values of the biomarker concentrations are scaled and the scaled values are introduced to a trained neural network, wherein the output values from the neural network tend toward the upper value in the presence of the disease and the output values tend toward the lower value, when the disease is absent.
WO 00/13024 refers to a method of predicting or diagnosing a skeletal disorder, wherein the level of at least one regulator or marker of bone remodeling is measured or estimated in the sample. The level is compared with a standard in order to determine whether the level of the regulator or marker falls within a range indicative of a potential to progress to exhibit overt symptoms of the skeletal disorder. For example, the method may comprise measuring of a bone resorption marker and a bone formation marker and determining the ratio of both markers.
WO 00/22437 refers to a method for predicting a treatment response and compliance of an individual after an anti-resorptive therapy, wherein the base line of a bone marker at the beginning of the anti-resorptive therapy is measured, a level of the bone marker after a first predetermined time period of anti-responsive therapy is measured and a probability of response in bone mass is generated after a second predetermined time period of the anti-resorptive therapy from a change of the bone marker level from a base line and the level of bone marker at either the base line or at the first predetermined time.
WO 01/22093 refers to a method for monitoring an effect of administration of a parathyroid hormone to a subject wherein a level of an enzyme indicative of an osteoblastic process of bone formation, a product of collagen biosynthesis, a product of collagen degradation or a combination thereof is measured and the level determined is correlated with an effect of administration of a parathyroid hormone.
WO 02/096284 refers to a method for diagnosis of bone disease wherein a mathematical function is used to relate the level of one or more biomarkers with a numerical value relating to one or more imaging descriptors comprising predetermined features from images defining bone disease characteristics to obtain a test value. The test value is compared with a control value, wherein a test value which differs from the control value by a predetermined amount is indicative of bone disease. The mathematical function may be selected from divisions, products, sums, logarithmic functions, exponential functions or combinations thereof.
WO 2004/059293 refers to a method of symptom-based diagnosis, wherein a test sample is analyzed for the presence or amount of a plurality of markers which are selected to identify the presence or absence of conditions within the differential diagnosis of a symptom. The presence or amount of markers in the test sample is correlated to the presence or absence of a condition.
WO 2007/092433 refers to a method with a predetermined level of predictability for assessing a risk of development of osteoporosis, pre-osteoporosis or bone fracture, wherein the level of one or more osteoporosis risk markers is measured and a clinically significant alteration in the level of the markers is measured, wherein the alteration indicates an increased risk of developing osteoporosis, pre-osteoporosis or bone fracture.
None of the above-identified methods, however, describes a method which is capable of assessing both, the balance and the overall dynamics of a physiological condition.
Hamwi et al. (Clin. Chem. Lab. Med 39 (2001), 414-417) describe the effects of hormone replacement therapy on biochemical markers of bone turnover. The overall bone turnover is expressed as area-product of the level of a bone formation marker and a bone resorption marker. Further, the resorption/formation ratio is determined. The results, however, are considered as preliminary and it is indicated that the clinical suitability of the marker ratio and area plot will have to be further tested.